Autoantigen-specific CD4+ T cells acquire an exhausted phenotype and persist in human antigen-specific autoimmune diseases
RNA-seq (gene expression) · human · 928 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 928 samples: 928 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Autoantigen-specific CD4(+) T cells acquire an exhausted phenotype and persist in human antigen-specific autoimmune diseasesImmunity · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE242232_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1012321 and SRA study SRP458160. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from the first 400 of 928 sample titles: 400 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7755942 T-AQP4_01 [L49750_Track-90536]
- GSM7755943 T-AQP4_01 [L49751_Track-90500]
- GSM7755944 T-AQP4_01 [L49752_Track-90399]
- GSM7755945 T-AQP4_01 [L49753_Track-90485]
- GSM7755946 T-AQP4_01 [L49755_Track-90465]
- GSM7755947 T-AQP4_01 [L49756_Track-90537]
- GSM7755948 T-AQP4_01 [L49757_Track-90458]
- GSM7755949 T-AQP4_01 [L49758_Track-90543]
- GSM7755950 T-AQP4_01 [L49759_Track-90505]
- GSM7755951 T-AQP4_01 [L49760_Track-90526]
- GSM7755952 T-AQP4_01 [L49762_Track-90403]
- GSM7755953 T-AQP4_01 [L49763_Track-90478]
- GSM7755954 T-AQP4_01 [L49764_Track-90457]
- GSM7755955 T-AQP4_01 [L49765_Track-90506]
- GSM7755956 T-AQP4_01 [L49766_Track-90368]
- GSM7755957 T-AQP4_01 [L49767_Track-90527]
- GSM7755958 T-AQP4_01 [L49768_Track-90445]
- GSM7755959 T-AQP4_01 [L49769_Track-90441]
- GSM7755960 T-AQP4_01 [L49770_Track-90436]
- GSM7755961 T-AQP4_01 [L49771_Track-90547]
- GSM7755962 T-AQP4_01 [L49772_Track-90542]
- GSM7755963 T-AQP4_01 [L49774_Track-90540]
- GSM7755964 T-AQP4_01 [L49775_Track-90425]
- GSM7755965 T-AQP4_01 [L49776_Track-90384]
- GSM7755966 T-AQP4_01 [L49777_Track-90521]
- GSM7755967 T-AQP4_01 [L49778_Track-90405]
- GSM7755968 T-AQP4_01 [L49779_Track-90440]
- GSM7755969 T-AQP4_01 [L49780_Track-90512]
- GSM7755970 T-AQP4_01 [L49781_Track-90469]
- GSM7755971 T-AQP4_01 [L49782_Track-90438]
- GSM7755972 T-AQP4_01 [L49783_Track-90421]
- GSM7755973 T-AQP4_01 [L49784_Track-90379]
- GSM7755974 T-AQP4_01 [L49786_Track-90358]
- GSM7755975 T-AQP4_01 [L49787_Track-90454]
- GSM7755976 T-AQP4_01 [L49788_Track-90497]
- GSM7755977 T-AQP4_01 [L49789_Track-90420]
- GSM7755978 T-AQP4_01 [L49790_Track-90397]
- GSM7755979 T-AQP4_01 [L49791_Track-90548]
- GSM7755980 T-AQP4_01 [L49792_Track-90359]
- GSM7755981 T-AQP4_01 [L49793_Track-90510]
+ 888 more — browse all 928 samples with per-sample file links →
- GSE267774 Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis 3076 samples shares cd4, phenotype
- GSE270739 Single-cell analysis of circulating autoreactive CD4 T cells of autoimmune hepatitis patients 62 samples shares cd4, autoimmune
- GSE282913 Gene Expression Analysis of CD4 T Cells in Autoimmune Pancreatitis: Treatment-Correlated Expression Profiles 45 samples shares cd4, autoimmune
- GSE218131 Oligoclonal CD4+CXCR5+ T cells with a cytotoxic phenotype in tonsils and blood 33 samples shares cd4, phenotype
- GSE263690 Brugia malayi filarial helminth-derived extracellular vesicles suppress antigen presenting cell functions and antigen-specific CD4+ T cell responses 20 samples shares cd4, antigen-specific
- GSE270732 The immune profile of circulating autoreactive CD4 T cells is imprinted through tissue activation during autoimmune liver diseases (Exp 1) 13 samples shares cd4, autoimmune
- GSE270734 The immune profile of circulating autoreactive CD4 T cells is imprinted through tissue activation during autoimmune liver diseases (Exp 3) 13 samples shares cd4, autoimmune
- GSE266862 Single-cell RNA sequencing comparison of CD4+, CD8+ and T-cell receptor γδ+ cutaneous T-cell lymphomas reveals subset-specific molecular phenotypes 44 samples shares cd4, phenotype
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.